Wan 3.0

export VENICE_API_KEY="your-api-key"

curl "https://api.venice.ai/api/v1/models?type=video" |
  jq '.data[] | select(.id | startswith("wan-3-0")) | {
    id,
    resolutions: .model_spec.constraints.resolutions,
    durations: .model_spec.constraints.durations,
    aspect_ratios: .model_spec.constraints.aspect_ratios,
    prompt_character_limit: .model_spec.constraints.prompt_character_limit,
    min_image_short_side: .model_spec.constraints.reference_image_min_short_side_pixels
  }'

curl https://api.venice.ai/api/v1/video/quote \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan-3-0-reference-to-video",
    "duration": "10s",
    "resolution": "720p"
  }'

{
  "quote": 1.3
}

curl https://api.venice.ai/api/v1/video/queue \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan-3-0-reference-to-video",
    "prompt": "A warm, sunlit pottery studio with wooden shelves of unglazed pots. 0-4s: medium shot. The woman from @Image1 lifts the teapot from @Image2 off a shelf with both hands and turns it so the gold handle catches the window light. She is silent. 4-10s: slow push-in to a close-up. She looks into the camera, smiles, and says only: \"This one took three firings.\" Quiet room tone and birdsong from the open window, no music.",
    "duration": "10s",
    "resolution": "720p",
    "aspect_ratio": "16:9",
    "reference_image_urls": [
      "https://docs.venice.ai/images/guides/wan-3-0/woman.webp",
      "https://docs.venice.ai/images/guides/wan-3-0/teapot.webp"
    ]
  }'

{
  "model": "wan-3-0-reference-to-video",
  "queue_id": "01a16b0b-e781-754d-8c54-8ade9c76edcd"
}

curl https://api.venice.ai/api/v1/video/retrieve \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan-3-0-reference-to-video",
    "queue_id": "01a16b0b-e781-754d-8c54-8ade9c76edcd"
  }' \
  --output response.bin

{
  "status": "PROCESSING",
  "average_execution_time": 450757,
  "execution_duration": 6611
}

{
  "model": "wan-3-0-reference-to-video",
  "prompt": "The woman from @Image1 stands beside a potter's wheel in a sunlit pottery studio. The camera moves like the camera in @Video1: one slow orbit around her from left to right, keeping her centred. Soft room tone, no music.",
  "duration": "5s",
  "resolution": "720p",
  "aspect_ratio": "16:9",
  "reference_image_urls": ["https://example.com/woman.webp"],
  "reference_video_urls": ["https://example.com/orbit.mp4"]
}

{
  "model": "wan-3-0-reference-to-video",
  "prompt": "Medium close-up in a sunlit pottery studio. The woman from @Image1 looks into the camera and says, in the voice from @Audio1: \"Welcome in. Mind the wet clay.\" Static camera, soft room tone, no music.",
  "duration": "5s",
  "resolution": "720p",
  "aspect_ratio": "16:9",
  "reference_image_urls": ["https://example.com/woman.webp"],
  "reference_audio_urls": ["https://example.com/voice.mp3"]
}

{
  "model": "wan-3-0-reference-to-video",
  "prompt": "Edit @Video1: make it winter. Snow covers the courtyard, the plinth, and the cypress trees, and light snow is falling. Keep the bust, the camera movement, and the framing unchanged.",
  "duration": "5s",
  "resolution": "720p",
  "aspect_ratio": "adaptive",
  "reference_video_urls": ["https://example.com/orbit.mp4"]
}

{
  "model": "wan-3-0-reference-to-video",
  "prompt": "Extend @Video1 by 5 seconds: the camera finishes its orbit, then rises slowly above the courtyard to reveal terracotta rooftops at golden hour. Same lighting and style, gentle wind, no music.",
  "duration": "10s",
  "resolution": "720p",
  "aspect_ratio": "16:9",
  "reference_video_urls": ["https://example.com/orbit.mp4"]
}

{
  "model": "wan-3-0-image-to-video",
  "prompt": "Time-lapse from morning to evening: daylight fades in the window, the pendant lamps switch on, and the shelves fill with teal-glazed pots. Static camera, no people.",
  "duration": "5s",
  "resolution": "720p",
  "aspect_ratio": "16:9",
  "image_url": "https://example.com/studio-day.webp",
  "end_image_url": "https://example.com/studio-evening.webp"
}

import base64
import os
import time
from pathlib import Path

import requests

BASE_URL = "https://api.venice.ai/api/v1"
HEADERS = {"Authorization": f"Bearer {os.environ['VENICE_API_KEY']}"}
MIME_TYPES = {".jpg": "image/jpeg", ".jpeg": "image/jpeg", ".png": "image/png", ".webp": "image/webp"}


def data_url(path):
    encoded = base64.b64encode(path.read_bytes()).decode()
    return f"data:{MIME_TYPES[path.suffix.lower()]};base64,{encoded}"


job_request = {
    "model": "wan-3-0-reference-to-video",
    "prompt": (
        "A warm, sunlit pottery studio with wooden shelves of unglazed pots. "
        "0-4s: medium shot. The woman from @Image1 lifts the teapot from @Image2 off a shelf with both hands "
        "and turns it so the gold handle catches the window light. She is silent. "
        "4-10s: slow push-in to a close-up. She looks into the camera, smiles, and says only: "
        '"This one took three firings." '
        "Quiet room tone and birdsong from the open window, no music."
    ),
    "duration": "10s",
    "resolution": "720p",
    "aspect_ratio": "16:9",
    "reference_image_urls": [data_url(Path("woman.webp")), data_url(Path("teapot.webp"))],
}

quote = requests.post(
    f"{BASE_URL}/video/quote",
    json={key: job_request[key] for key in ("model", "duration", "resolution")},
)
quote.raise_for_status()
print(f"Estimated cost: ${quote.json()['quote']:.2f}")

queued = requests.post(f"{BASE_URL}/video/queue", headers=HEADERS, json=job_request)
queued.raise_for_status()
job = queued.json()
print(f"Queued {job['queue_id']}")

started = time.monotonic()
deadline = started + 20 * 60
while time.monotonic() < deadline:
    result = requests.post(
        f"{BASE_URL}/video/retrieve",
        headers=HEADERS,
        json={
            "model": job["model"],
            "queue_id": job["queue_id"],
            "delete_media_on_completion": True,
        },
    )

    content_type = result.headers.get("Content-Type", "").split(";")[0].strip()
    if content_type == "video/mp4":
        output = Path("pottery-studio.mp4")
        output.write_bytes(result.content)
        print(f"Saved {output} after {time.monotonic() - started:.0f}s")
        break

    body = result.json()
    if not result.ok:
        # Terminal failure. Polling again returns the same error.
        print(f"{result.status_code}: {body.get('error')}")
        raise SystemExit(1)

    if body.get("status") != "PROCESSING":
        print(body)
        raise SystemExit(1)

    time.sleep(15)
else:
    raise SystemExit(
        f"Still processing after 20 minutes. Poll retrieve again later with queue_id={job['queue_id']}."
    )